Typically, coherent optical receivers may utilize oversampling (e.g. the signal sampling rates are higher than an optical system's symbol rate) to enable fractionally spaced equalization of chromatic dispersion (CD) and/or polarization mode dispersion (PMD). In contrast to T-spaced (baud-spaced) equalizers, fractionally spaced equalizers (FSE) increase the tolerance against sampling phase errors and minimize noise enhancement arising from spectral nulls during aliasing and from spectrum folding at the equalizer input. Specifically, an FSE may reduce noise by sampling the received signal at a rate higher than the symbol rate to limit the amount of aliasing in the received signal. In addition, an adaptive FSE may correct for sampling phase error by interpolating and thereby reducing the effect of sampling phase error on noise. Unfortunately, current FSEs (e.g. T/2 spaced FSEs) may be relatively more complex, consume more power, and/or are more costly to implement within high baud rate optical communication systems.
U.S. Pat. No. 9,112,742 (Ali Shah et al), which is incorporated herein by reference in its entirety, discloses an apparatus having a processor coupled to a memory for executing instructions to cause the apparatus to receive an incoming signal at a sampling rate that is greater than a symbol rate of the incoming signal, replicate a plurality of data streams from the incoming signal, apply a plurality of fractional delays for the data streams, and perform an adaptive equalization on a plurality of data blocks generated from the data streams. FIG. 1 depicts an apparatus 10, according to the teachings of U.S. Pat. No. 9,112,742, which includes a fractional delay filter (FDF) 20, an adaptive filter 30 downstream of the FDF, a symbol detector 40 downstream of the adaptive filter 30 and a filter coefficient update component 50 which receives an error signal from the symbol detector 40. The filter coefficient update component 50 updates the filter coefficients of the adaptive filter 30.
The adaptive filter 30 does not operate as a conventional linear filter because of the preceding FDF 20. In other words, the input data to the adaptive filter 30 is not continuous. For example, two consecutive input vectors to the adaptive filter 30 do not represent an integer sample shift. FIG. 2 presents an example of adaptive filter input data vector without an FDF in which the adaptive filter behaves as a conventional linear filter. This is due to the fact that the input data vector at consecutive sampling instants, for example at sampling instant ‘n’ and ‘n+1’, has one complete sample shift as shown in FIG. 2. In comparison, FIG. 3 presents input with the FDF in which the data continuity is affected because of the FDF. The data discontinuity makes it difficult to implement low-complexity architectures for the adaptive filter 30 that are known to reduce the complexity of the filtering operation.
It would thus desirable to provide an improved adaptive fractionally spaced equalizer with non-integer sampling that enables a low-complexity architecture to be implemented for the adaptive filter.